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Joint estimation of fast-updating state and intermittent-updating state

机译:快速更新状态和间歇性更新状态的联合估计

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This paper formulates a joint estimation problem of fast-updating state and intermittent-updating state in multi-rate systems. The original multi-rate system is first transformed into a single-rate one. Since the direct use of Kalman filtering method on the lifted system will result in the Kalman smoother, the causality constraints must be taken into account in the filter design. Then, based on the lifted system a multi-rate filter (MRF) with causality constraints is derived in the linear minimum mean squared error (LMMSE) sense using the orthogonality principle. A numerical example is given to show the effectiveness of the proposed filter.
机译:本文在多速率系统中制定了快速更新状态和间歇更新状态的联合估计问题。原始多速率系统首先将其转换为单速率。由于在提升系统上直接使用卡尔曼滤波方法将导致卡尔曼更顺畅,因此必须在过滤器设计中考虑因果关系约束。然后,基于提升系统,使用正交原理,在线性最小平均平均误差(LMMSE)isse中导出具有因果关系约束的多速率滤波器(MRF)。给出了数值例子来显示所提出的滤波器的有效性。

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